72 citations · 173 across the 9 of their papers we have counts for
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q-bio.NC2023★ 2 cited
Expressive dynamics models with nonlinear injective readouts enable reliable recovery of latent features from neural activity
Christopher Versteeg, Andrew R. Sedler, Jonathan D. McCart +1
The advent of large-scale neural recordings has enabled new methods to discover the computational mechanisms of neural circuits by understanding the rules that govern how their sta…
cs.LG2023
lfads-torch: A modular and extensible implementation of latent factor analysis via dynamical systems
Andrew R. Sedler, Chethan Pandarinath
Latent factor analysis via dynamical systems (LFADS) is an RNN-based variational sequential autoencoder that achieves state-of-the-art performance in denoising high-dimensional neu…